1. Technical Field
The present invention relates generally to an improved data processing system and in particular to a method and apparatus for performing handwriting recognition. Still more particularly, the present invention provides a method and apparatus for scaling handwritten character input for facilitating handwriting recognition.
2. Description of Related Art
In the field of handwriting recognition, various approaches have been taken by software vendors to provide more accurate recognition of handwriting samples. Written languages that have large character sets, e.g., the Chinese and Korean languages, are particularly problematic for software vendors to develop efficient handwriting recognition algorithms. The Chinese language, for example, includes thousands of characters. Accordingly, a reference character dictionary for performing handwriting recognition of the Chinese language necessarily includes thousands of entries. The data size of the characters maintained in the reference dictionary limits the efficiency for performing handwriting analysis of written Chinese characters.
Handwriting recognition solutions require sampling handwritten character strokes during input of the strokes and comparing the samples with reference characters maintained in a reference character dictionary. For example, many handwriting recognition algorithms require construction of an image, such as a bitmap, of the handwritten character for interrogation of a reference character dictionary. For languages including large character sets, thousands of comparisons may be made to identify a potential match. Such techniques are data-intensive and require large processing capacity to effectively implement a handwriting recognition algorithm.
A particular problem encountered during comparison of handwritten characters with characters of a reference character dictionary results from variations in the character size input by a user. For example, a user may write a character that consumes a majority of a capture area of the input device. Another user may write the same character at a size that only consumes a fraction of the capture area. The character data of the reference character dictionary is derived from a character set of uniform size. Thus, comparisons of handwritten characters with characters of a reference character dictionary will often result in different character matches due to variations in the character input size.
It would be advantageous to provide a handwriting recognition technique that scales character input to improve comparison results of handwritten characters with characters of a reference character dictionary. It would be further advantageous to provide a handwriting recognition technique for scaling a handwritten character stroke parameter according to an input area in which the handwritten stroke was supplied. It would still be further advantageous to rescale a handwritten stroke parameter according to a recalculated input area after entry of subsequent handwritten character strokes.